9,083 research outputs found

    Cash Versus In-Kind Transfers: Comparative Differences and Individual Best Practices to Benefit Recipient Communities

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    This research paper seeks to compare cash and in-kind transfers in the context of foreign poverty aid to determine which transfer style is most beneficial and to evaluate long-term best practices of each kind to more positively benefit the recipient communities. It does this by comparing arguments for and against each transfer model. The first argument discusses the differences in distribution costs between the two models. The second compares the cash transfer’s strong concept of choice with in-kind transfer’s typical style of controlled consumption of goods. The second argument discusses the timing and impact of targeting communities in connection to each transfer style. Finally, the last argument discusses the contrasting macroeconomic impact each style has on local markets. Cash transfers are predetermined cash donations given either as a lump sum or in periodic transfers. Conversely, in-kind transfers are direct transfers of physical goods distributed to households. This paper maintains that both transfer styles have the capability of being beneficial if they are planned and executed with extensive knowledge of the unique local community, its needs, the economic and social effects of each transfer style, and a purposeful design aimed at long-term growth and empowerment of communities

    Robustness of 3D Deep Learning in an Adversarial Setting

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    Understanding the spatial arrangement and nature of real-world objects is of paramount importance to many complex engineering tasks, including autonomous navigation. Deep learning has revolutionized state-of-the-art performance for tasks in 3D environments; however, relatively little is known about the robustness of these approaches in an adversarial setting. The lack of comprehensive analysis makes it difficult to justify deployment of 3D deep learning models in real-world, safety-critical applications. In this work, we develop an algorithm for analysis of pointwise robustness of neural networks that operate on 3D data. We show that current approaches presented for understanding the resilience of state-of-the-art models vastly overestimate their robustness. We then use our algorithm to evaluate an array of state-of-the-art models in order to demonstrate their vulnerability to occlusion attacks. We show that, in the worst case, these networks can be reduced to 0% classification accuracy after the occlusion of at most 6.5% of the occupied input space.Comment: 10 pages, 8 figures, 1 tabl

    Banking and financial crises in United States history: what guidance can history offer policymakers?

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    This paper assesses the validity of comparisons between the current financial crisis and past crises in the United States. We highlight aspects of two National Banking Era crises (the Panic of 1873 and the Panic of 1907) that are relevant for comparison with the Panic of 2008. In 1873, overinvestment in railroad debt and the default of railroad companies on that debt led to the failure of numerous brokerage houses, precursor to the modern investment bank. During the Panic of 1907, panic-related deposit withdrawals centered on the less regulated trust companies, which had only indirect access to the existing lender of last resort, similar to investment banks in 2008. The popular press has made numerous references to the banking crises of the Great Depression as relevant comparisons to the recent crisis. This paper argues that such an analogy is inaccurate. The previous banking crises in U.S. history reflected widespread depositor withdrawals whereas the recent panic arose from counterparty solvency fears and large counterparty exposures among large complex financial intermediaries. In historical incidents, monitoring counterparty exposures was standard banking practice and the exposures were smaller. From this perspective, the lessons from the past appear less directly relevant for the current crisis.Financial crises - United States ; Systemic risk

    A MLSA-MLST scheme to investigate the real evolutionary dynamics within the Ralstonia solanacearum species complex : [P01-06]

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    The soilborne beta-proteobacterium #Ralstonia solanacearum# is the causing agent of major plant diseases (bacterial wilt on several species, potato brown rot, Moko disease of banana) within tropical and subtropical areas, affecting both cash and subsistence crops. This species complex is constituted of four phylotypes, correlated with the geographical origin of strains (I, Asian; II, American; III, African; IV, Indonesian). Each phylotype is further subdivided in sequevars, on the basis of sequence divergence of the endoglucanase gene (egl); some of these sequevars have been associated to specific ecological features (host range, virulence at cool temperatures). Genomic structure and phylogeny of this species complex is now well understood, thank to recent CGH studies (2) and sequencing of several complete genomes. The subdivision in four phylotypes was clearly demonstrated, but the existence of different clades within each phylotype still had to be validated. The high genotypic and phenotypic plasticity of this organism has been illustrated by emergence of new pathogenic variants (3). It was demonstrated that this bacterium, naturally competent, is potentially subjected to recombination and horizontal genetic transfer (HGT). However, the real degrees of recombination occurring in natural populations, the dominant reproductive mode of this bacterium, the selection pressures structuring these populations, are still largely unknown. To clarify both phylogeny and evolutionary dynamics of the #R. solanacearum# species complex, we developed a MLSA-MLST scheme on a collection of 88 #R.solanacearum# strains classified in the four phylotypes and 51 sequevars described to date, and one strain of each of the close species #R. syzygii#, #R. pickettii#, #R. mannitolylitica# and #R. insidiosa#. Genes were chosen following previous MLSA approach (1) and reference studies; all were (i) evenly distributed across the two replicons, and distant of at least 100 kb, (ii) present in one single copy in the genomes. They consisted in six housekeeping genes (ppsA, rplB, gdhA, leuS, adk, gyrB), the DNA mismatch repair gene mutS, and two virulence-associated genes (egl, fliC). Phylogenies reconstructed from individual genes, and with concatenated genes, were globally congruent with each other. They allowed identifying several phylogenetically differentiated subdivisions, named clades, within some of the phylotypes. Within the phylotype I, one single clade was found. Within the phylotype II, the subclusters IIA and IIB were validated and four clades were found: (i) "brown rot" IIB/sequevar 1, 2 and Moko sequevar 3; (ii) sequevar 4 (Moko and emergent strains); (iii) "South-Eastern USA biovar 1" strains, or sequevar 7; (iv) "Antillean biovar 1" strains, and Moko sequevar 6 strains. Within the phylotype III, two clades were identified: (i) Austral Africa and Indian Ocean strains, and (ii) Central and Western African strains. Within the phylotype IV, two clades were found: (i) blood disease bacterium and Indonesian #R. solanacearum# strains, (ii) #R. syzygii#. The population structure of #R. solanacearum# was assessed by the MLST approach, at the global scale and at the phylotype scale. The global population structure appeared to be clonal; however phylotypes clearly differed in structure: phylotypes I and III displayed a recombining population structure, whereas phylotype II was highly clonal. Analyses of the different evolutionary forces structuring the #R. solanacearum# species complex are ongoing, and will be presented and discussed. A collection of reference strains for each clade will be proposed. (Résumé d'auteur

    Clustering of Local Group distances: publication bias or correlated measurements? I. The Large Magellanic Cloud

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    The distance to the Large Magellanic Cloud (LMC) represents a key local rung of the extragalactic distance ladder. Yet, the galaxy's distance modulus has long been an issue of contention, in particular in view of claims that most newly determined distance moduli cluster tightly - and with a small spread - around the "canonical" distance modulus, (m-M)_0 = 18.50 mag. We compiled 233 separate LMC distance determinations published between 1990 and 2013. Our analysis of the individual distance moduli, as well as of their two-year means and standard deviations resulting from this largest data set of LMC distance moduli available to date, focuses specifically on Cepheid and RR Lyrae variable-star tracer populations, as well as on distance estimates based on features in the observational Hertzsprung-Russell diagram. We conclude that strong publication bias is unlikely to have been the main driver of the majority of published LMC distance moduli. However, for a given distance tracer, the body of publications leading to the tightly clustered distances is based on highly non-independent tracer samples and analysis methods, hence leading to significant correlations among the LMC distances reported in subsequent articles. Based on a careful, weighted combination, in a statistical sense, of the main stellar population tracers, we recommend that a slightly adjusted canonical distance modulus of (m-M)_0 = 18.49 +- 0.09 mag be used for all practical purposes that require a general distance scale without the need for accuracies of better than a few percent.Comment: 35 pages (AASTeX preprint format), 5 postscript figures; AJ, in press. For full database of LMC distance moduli, see http://astro-expat.info/Data/pubbias.htm
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